Meaning in Context: Ontologically and linguistically motivated representations of objects and events

Abstract

Context is pervasive in all activities involving human beings as well as computer systems. It affects numerous aspects of our lives: how we understand the world, our communication, as well as the planning, carrying, and outcomes of activities. When focusing on understanding natural language, context plays a pivotal role that affects various facets ranging from the interpretation of speech signal to the identification of word meaning, composition of phrases and sentences as well as the intention of the discourse.Context impacts the conceptualisation of human experience. Objects and events assume different cognitive salience according to their context of occurrence, thus determining access to partial relevant information rather than to all information. Understanding a piece of natural language requires a continuous interaction between abstract conceptualisations and their actual use or occurrence in a specific communicative situation. A possible example to clarify this distinction could be that of an orange being passed between two children, and that of the same orange peeled on a table: in the former context the roundness of the object prevails over other features, traits, or aspects that characterise the concept of "the fruit orange". In the latter context, the edible features are those mostly relevant and conveyed. Similar mechanisms are at play with events. A well known example is that of "commercial events". Different surface forms (i.e., verbs) can be used to express related, if not the same, knowledge about the same scenario. For instance, the verbs buy and sell offer different interpretations of the same event, where none of them puts the focus on the object of the transaction, but rather on its participant. An extreme situation, in this case, is when different interpretations are imposed on the same event. For instance, a fatal shooting by the police can be interpreted as necessary self-defence (by the police officers) or as a murder (by the friends and family of the victim). Similar selectional mechanisms underlie figurative uses of word meanings, such as metonymy and metaphors among others, that intrinsically characterize the interface between knowledge and language -see the work by Gangemi et al. (2018) for a recent study on the ontological treatment of conceptual metaphors.

Violence detection explanation via semantic roles embeddings

“…One chief motivation for building explainable AI systems is thus the need to check systems behavior, to ensure that systems perform as expected. This need has become particularly relevant in the last few years, that have witnessed the spread of deep learning based neural networks, in that these are featured by strong predictive power, at the expense of the interpretability of their output [13,14]. In this work we investigate one such critical application domain: the categorization of electronic medical records (EMR) data, where an Information Extraction approach has been devised to complement the output of the deep neural network performing the categorization step.…”

ER documents categorization and explanation

“…One chief motivation for building explainable AI systems is thus the need to check systems behavior, to ensure that systems perform as expected. This need has become particularly relevant in the last few years, that have witnessed the spread of deep learning based neural networks, in that these are featured by strong predictive power, at the expense of the interpretability of their output [11,12]. In this work we investigate one such critical application domain: the categorization of electronic medical records (EMR) data, where an Information Extraction approach has been devised to complement the output of the deep neural network performing the categorization step.…”